docs: def print_portfolio_info(returns, avg_rets, weights):
      """
      Print information on expected portfolio performance.
      """
      ret = (weights * avg_rets).sum()
      std = (weights * returns).sum(1).std()
      sharpe = ret / std
      print("Optimal weights:\n{}\n".format(weights))
      print("Expected return:   {}".format(ret))
      print("Expected variance: {}".format(std**2))
      print("Expected Sharpe:   {}".format(sharpe))